MétaCan
Menu
Back to cohort
Record W4392863223 · doi:10.1017/s0950268824000475

The molecular epidemiology of hepatitis E virus genotype 3 in Canada

2024· article· en· W4392863223 on OpenAlexaffabout
Jamie Borlang, Donald G. Murphy, Jennifer Harlow, Carla Osiowy, Neda Nasheri

Bibliographic record

VenueEpidemiology and Infection · 2024
Typearticle
Languageen
FieldMedicine
TopicHepatitis Viruses Studies and Epidemiology
Canadian institutionsUniversity of OttawaHealth CanadaInstitut National de Santé Publique du QuébecPublic Health Agency of Canada
Fundersnot available
KeywordsHepatitis E virusGenotypeMolecular epidemiologyVirologyEpidemiologyBiologyCaliciviridaeVirusZoonosisOutbreakViral diseaseMedicineGeneGenetics

Abstract

fetched live from OpenAlex

Autochthonous hepatitis E virus (HEV) infection is increasingly reported in industrialized countries and is mostly associated with zoonotic HEV genotype 3 (HEV-3). In this study, we examined the molecular epidemiology of 63 human clinical HEV-3 isolates in Canada between 2014 and 2022. Fifty-five samples were IgM positive, 45 samples were IgG positive and 44 were IgM and IgG positive. The majority of the isolates belong to the subtypes 3a, 3b, and 3j, with high sequence homology to Canadian swine and pork isolates. There were a few isolates that clustered with subtypes 3c, 3e, 3f, 3h, and 3g, and an isolate from chronic infection with a rabbit strain (3ra). Previous studies have demonstrated that the isolates from pork products and swine from Canada belong to subtypes 3a and 3b, therefore, domestic swine HEV is likely responsible for the majority of clinical HEV cases in Canada and further support the hypothesis that swine serve as the main reservoirs for HEV-3 infections. Understanding the associated risk of zoonotic HEV infection requires the establishment of sustainable surveillance strategies at the interface between humans, animals, and the environment within a One-Health framework.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.037
GPT teacher head0.322
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueEpidemiology and InfectionSame topicHepatitis Viruses Studies and EpidemiologyFrench-language works237,207